It has been known in the art for some years that videogrammetry software, such as Photosynth available from Microsoft and 123D Catch available from Autodesk, can be used to generate a three-dimensional mesh from a plurality of images acquired by a camera moving relative to a target object. Conventional videogrammetry practice, conducted from an aerial perspective, or in a far-range setting, may include target objects such as, for example, forests (for ecological analysis), historic sites, parking lot capture, and crowd security analysis. Conventional videogrammetry conducted from a midrange or close range, may include targeting individual plants, statutes, pottery, fossils, utensils, weapons, reverse engineering of vehicles, and face recognition.
Videogrammetry software functions to: (i) match various interest points across the plurality of images, (ii) infer camera exterior orientation, (iii) interpolate the matched interest points to extract more points, and (iv) generate a three-dimensional mesh. However, conventional videogrammetry methods may not produce satisfactory results for certain objects. For example, the videogrammetry process performs best on surfaces that are non-reflective and highly textured.
Moreover, the image capture must follow certain criteria. The surface of the object of interest should be stationary. Lighting is also important. The lighting should be consistent from one acquired image to the next, and should minimize glare or deep shadows. Image overlap is also essential as, ideally, the acquired images should have at least 50% scene overlap from image to image. Finally, the images should capture the object in an orderly fashion by following a predetermined path, for example, such as by encircling the object of interest.
Conventional videogrammetry methods thus are not particularly well-suited for extremely close (i.e., hyperclose) range image capture of objects such as tire treads, although such objects may present highly textured features at hyperclose range and may seem to be well-suited for three-dimensional structure recovery. What is needed is a method and system for ensuring that scene capture criteria are met, and that provide for consistent lighting, image overlap, and object stability.